A Fuzzy Hierarchical Clustering Based on the Maximum Distance to the Center of Gravity
DOI:
https://doi.org/10.26821/ijshre.14.10.2026.141001Kata Kunci:
Automatic classification, Fuzzy hierarchical clustering, CAHFD, Maximum distance to the center of gravity, Membership degree, Corrected Distance (DCo), Dendrogram, Fuzzy C-meansAbstrak
This paper proposes a new approach to Fuzzy Agglomerative Hierarchical Clustering based on the maximum distance to the center of gravity (CAHFD), falling within the field of automatic classification. This contribution introduces a hierarchical approach based on a membership function using the maximum distance to the center of gravity. Furthermore, the paper presents an independent innovation: a new distance expression, the Corrected Distance (DCo), combining the JM (or JM) index and the Euclidean distance. Unlike non-hierarchical partitioning methods such as fuzzy C-means, which do not produce any dendrogram, CAHFD incorporates a tree-like structure that preserves nuanced fuzziness regarding boundary objects and faithfully restores the topological progressivity of the data.
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